Unite.AI

AUGUST 4, 2023

In this article, we will delve deeper into these issues, exploring the advanced techniques of prompt engineering with Langchain, offering clear explanations, practical examples, and step-by-step instructions on how to implement them. Prompts play a crucial role in steering the behavior of a model.

Prompt Engineer 245

Prompt Engineer Prompt Engineering Python NLP 245

Unite.AI

JANUARY 11, 2024

More recent methods based on pre-trained language models like BERT obtain much better context-aware embeddings. Existing methods predominantly use smaller BERT-style architectures as the backbone model. For model training, they opted for fine-tuning the open-source 7B parameter Mistral model instead of smaller BERT-style architectures.

Large Language Models 147

Large Language Models Prompt Engineer Prompt Engineering BERT 147

Unite.AI

SEPTEMBER 20, 2023

To install and import the library, use the following commands: pip install -q transformers from transformers import pipeline Having done that, you can execute NLP tasks starting with sentiment analysis, which categorizes text into positive or negative sentiments. We choose a BERT model fine-tuned on the SQuAD dataset.

LLM 342

LLM BERT NLP Python 342

Artificial Corner

JULY 30, 2023

Machine translation, summarization, ticket categorization, and spell-checking are among the examples. Prompts design is a process of creating prompts which are the instructions and context that are given to Large Language Models to achieve the desired task. RoBERTa (Robustly Optimized BERT Approach) — developed by Facebook AI.

Large Language Models 85

Large Language Models LLM Natural Language Processing Deep Learning 85

Unite.AI

AUGUST 8, 2023

These advanced AI deep learning models have seamlessly integrated into various applications, from Google's search engine enhancements with BERT to GitHub’s Copilot, which harnesses the capability of Large Language Models (LLMs) to convert simple code snippets into fully functional source codes.

Generative AI 243

Generative AI ChatGPT Neural Network Convolutional Neural Networks 243

Flipboard

DECEMBER 6, 2023

Types of summarizations There are several techniques to summarize text, which are broadly categorized into two main approaches: extractive and abstractive summarization. In this post, we focus on the BERT extractive summarizer. It works by first embedding the sentences in the text using BERT.

BERT 128

BERT Large Language Models Artificial Intelligence Artificial Intelligence 128

Snorkel AI

AUGUST 17, 2023

Users can easily constrain an LLM’s output with clever prompt engineering. That minimizes the chance that the prompt will overrun the context window, and also reduces the cost of high-volume runs. Its categorical power is brittle. BERT for misinformation. The largest version of BERT contains 340 million parameters.

Generative AI 52

Generative AI BERT LLM Prompt Engineer 52